from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 53.948621 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 26.714052 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 56.286701 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 49.739476 |
| KMeans_tall | 0.0 | 1.0 | 42.166554 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 18.936000 |
| KMeans_short | 0.0 | 0.0 | 19.896913 |
| daal4py_KMeans_short | 0.0 | 0.0 | 9.093467 |
| LogisticRegression | 0.0 | 1.0 | 3.360418 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 55.243689 |
| Ridge | 0.0 | 0.0 | 48.074542 |
| daal4py_Ridge | 0.0 | 0.0 | 15.345816 |
| total | 0.0 | 32.0 | 38.884086 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.149 | 0.002 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.498 | 0.001 | 0.299 | 0.003 | See |
| 1 | KNeighborsClassifier | predict | 0.167 | 0.014 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 0.085 | 0.001 | 1.954 | 0.162 | See |
| 2 | KNeighborsClassifier | predict | 25.681 | 1.056 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 2.038 | 0.007 | 12.599 | 0.520 | See |
| 3 | KNeighborsClassifier | fit | 0.149 | 0.004 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.486 | 0.004 | 0.306 | 0.008 | See |
| 4 | KNeighborsClassifier | predict | 0.192 | 0.012 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 0.0 | 0.085 | 0.001 | 2.260 | 0.139 | See |
| 5 | KNeighborsClassifier | predict | 35.886 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 0.0 | 2.028 | 0.008 | 17.696 | 0.068 | See |
| 6 | KNeighborsClassifier | fit | 0.134 | 0.000 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.484 | 0.001 | 0.277 | 0.001 | See |
| 7 | KNeighborsClassifier | predict | 0.187 | 0.016 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 0.0 | 0.085 | 0.000 | 2.187 | 0.183 | See |
| 8 | KNeighborsClassifier | predict | 35.764 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 0.0 | 2.106 | 0.010 | 16.981 | 0.083 | See |
| 9 | KNeighborsClassifier | fit | 0.131 | 0.000 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.486 | 0.003 | 0.270 | 0.002 | See |
| 10 | KNeighborsClassifier | predict | 0.188 | 0.001 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 0.085 | 0.000 | 2.213 | 0.017 | See |
| 11 | KNeighborsClassifier | predict | 13.208 | 0.019 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 2.023 | 0.010 | 6.528 | 0.035 | See |
| 12 | KNeighborsClassifier | fit | 0.132 | 0.000 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.484 | 0.001 | 0.272 | 0.001 | See |
| 13 | KNeighborsClassifier | predict | 0.203 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 0.0 | 0.086 | 0.001 | 2.365 | 0.026 | See |
| 14 | KNeighborsClassifier | predict | 24.939 | 0.016 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 0.0 | 2.041 | 0.012 | 12.218 | 0.074 | See |
| 15 | KNeighborsClassifier | fit | 0.143 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.485 | 0.004 | 0.295 | 0.006 | See |
| 16 | KNeighborsClassifier | predict | 0.207 | 0.003 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 0.0 | 0.086 | 0.001 | 2.416 | 0.041 | See |
| 17 | KNeighborsClassifier | predict | 25.054 | 0.118 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 0.0 | 2.095 | 0.010 | 11.958 | 0.081 | See |
| 18 | KNeighborsClassifier | fit | 0.062 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.111 | 0.003 | 0.563 | 0.016 | See |
| 19 | KNeighborsClassifier | predict | 0.020 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.006 | 0.000 | 3.277 | 0.455 | See |
| 20 | KNeighborsClassifier | predict | 21.540 | 0.008 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.317 | 0.002 | 67.891 | 0.443 | See |
| 21 | KNeighborsClassifier | fit | 0.061 | 0.000 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.110 | 0.003 | 0.556 | 0.016 | See |
| 22 | KNeighborsClassifier | predict | 0.030 | 0.001 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.007 | 0.001 | 4.494 | 0.621 | See |
| 23 | KNeighborsClassifier | predict | 31.879 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.321 | 0.002 | 99.308 | 0.695 | See |
| 24 | KNeighborsClassifier | fit | 0.061 | 0.000 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.110 | 0.000 | 0.558 | 0.005 | See |
| 25 | KNeighborsClassifier | predict | 0.031 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 4.766 | 0.855 | See |
| 26 | KNeighborsClassifier | predict | 32.130 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.379 | 0.004 | 84.700 | 0.843 | See |
| 27 | KNeighborsClassifier | fit | 0.063 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.111 | 0.003 | 0.568 | 0.017 | See |
| 28 | KNeighborsClassifier | predict | 0.016 | 0.000 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.006 | 0.001 | 2.448 | 0.217 | See |
| 29 | KNeighborsClassifier | predict | 10.563 | 0.009 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.323 | 0.008 | 32.682 | 0.837 | See |
| 30 | KNeighborsClassifier | fit | 0.062 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.111 | 0.003 | 0.563 | 0.013 | See |
| 31 | KNeighborsClassifier | predict | 0.025 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.006 | 0.000 | 4.073 | 0.266 | See |
| 32 | KNeighborsClassifier | predict | 21.199 | 0.008 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.319 | 0.004 | 66.366 | 0.731 | See |
| 33 | KNeighborsClassifier | fit | 0.062 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.110 | 0.001 | 0.568 | 0.004 | See |
| 34 | KNeighborsClassifier | predict | 0.026 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.006 | 0.000 | 4.054 | 0.340 | See |
| 35 | KNeighborsClassifier | predict | 21.448 | 0.017 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.382 | 0.003 | 56.175 | 0.438 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 3.100 | 0.014 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.752 | 0.013 | 4.124 | 0.076 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 13.677 | 7.313 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.472 | 0.004 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.108 | 0.002 | 4.358 | 0.095 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 3.136 | 0.016 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.771 | 0.005 | 4.067 | 0.033 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 11.687 | 6.180 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.863 | 0.004 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.201 | 0.001 | 4.300 | 0.036 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.137 | 0.024 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.787 | 0.023 | 3.986 | 0.120 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.011 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 11.165 | 4.229 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.827 | 0.017 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.607 | 0.016 | 4.660 | 0.126 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.102 | 0.029 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.798 | 0.017 | 3.886 | 0.092 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 6.919 | 3.742 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.753 | 0.003 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.115 | 0.001 | 6.555 | 0.086 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.133 | 0.033 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.752 | 0.017 | 4.167 | 0.106 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 7.907 | 3.650 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.452 | 0.010 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.207 | 0.004 | 7.019 | 0.146 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.141 | 0.027 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.791 | 0.016 | 3.973 | 0.088 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.010 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 10.147 | 3.497 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 4.779 | 0.014 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.633 | 0.004 | 7.546 | 0.057 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.419 | 0.006 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.541 | 0.005 | 2.624 | 0.027 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 0.0 | 0.000 | 0.000 | 18.977 | 14.735 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.030 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 0.0 | 0.001 | 0.000 | 34.822 | 14.526 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.433 | 0.011 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.533 | 0.011 | 2.689 | 0.058 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 0.0 | 0.000 | 0.000 | 17.744 | 12.446 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.030 | 0.000 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 0.0 | 0.001 | 0.001 | 21.488 | 8.282 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.351 | 0.006 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.530 | 0.014 | 2.549 | 0.070 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 0.0 | 0.000 | 0.000 | 20.580 | 14.655 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.053 | 0.004 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 0.0 | 0.008 | 0.001 | 6.782 | 1.113 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.370 | 0.016 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.536 | 0.013 | 2.559 | 0.070 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 0.0 | 0.000 | 0.000 | 5.927 | 4.724 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.027 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 0.0 | 0.001 | 0.000 | 23.743 | 9.060 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.369 | 0.011 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.533 | 0.019 | 2.567 | 0.093 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 0.0 | 0.000 | 0.000 | 5.844 | 4.640 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.029 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 0.0 | 0.001 | 0.000 | 24.543 | 6.325 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.360 | 0.008 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.540 | 0.007 | 2.517 | 0.037 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 0.0 | 0.000 | 0.000 | 5.784 | 4.346 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.058 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 0.0 | 0.008 | 0.001 | 7.404 | 1.089 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.649 | 0.011 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.503 | 0.041 | 1.290 | 0.108 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.082 | 1.615 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.681 | 1.038 | See |
| 3 | KMeans_tall | fit | 0.576 | 0.008 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.456 | 0.039 | 1.263 | 0.109 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.087 | 1.521 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.817 | 1.248 | See |
| 6 | KMeans_tall | fit | 6.849 | 0.072 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.136 | 0.028 | 2.184 | 0.030 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.707 | 1.381 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.251 | 1.067 | See |
| 9 | KMeans_tall | fit | 6.232 | 0.061 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.937 | 0.018 | 2.121 | 0.024 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.551 | 1.143 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.920 | 0.873 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.349 | 0.030 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.114 | 0.003 | 3.049 | 0.274 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.180 | 1.495 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.282 | 0.343 | See |
| 3 | KMeans_short | fit | 0.130 | 0.001 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.050 | 0.001 | 2.606 | 0.061 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.979 | 1.295 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.196 | 0.420 | See |
| 6 | KMeans_short | fit | 0.854 | 0.033 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 22.0 | NaN | 22.0 | NaN | 0.401 | 0.015 | 2.131 | 0.114 | See |
| 7 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.634 | 0.997 | See |
| 8 | KMeans_short | predict | 0.007 | 0.002 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 5.221 | 1.971 | See |
| 9 | KMeans_short | fit | 0.244 | 0.029 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 17.0 | NaN | 22.0 | NaN | 0.191 | 0.030 | 1.280 | 0.251 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.743 | 0.971 | See |
| 11 | KMeans_short | predict | 0.007 | 0.003 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 5.417 | 2.055 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 11.631 | 0.039 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 11.322 | 0.023 | 1.027 | 0.004 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.422 | 0.478 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.961 | 0.493 | See |
| 3 | LogisticRegression | fit | 0.790 | 0.014 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [27] | 0.775 | 0.017 | 1.019 | 0.029 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.000 | 0.132 | 0.086 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.004 | 0.001 | 0.523 | 0.228 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1.775 | 0.046 | 100000 | 100000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.959 | 0.005 | 1.851 | 0.049 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 100000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.616 | 0.624 | See |
| 2 | Ridge | predict | 0.001 | 0.000 | 100000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.001 | 0.000 | 0.834 | 0.319 | See |
| 3 | Ridge | fit | 1.135 | 0.009 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.245 | 0.002 | 4.636 | 0.052 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.641 | 0.670 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.662 | 0.424 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.12.so",
"prefix": "libopenblas",
"user_api": "blas",
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"version": "0.3.12",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
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}
],
"cpu_count": 2
}